Coherency Approach for Dynamic Equivalents of Large Power Systems
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Bibliographic record
Abstract
This paper presents a method of identifying coher- ent generators on the basis of slow coherency concept, and constructing of dynamic equivalent for large electric power system. We will first describe the slow coherency technique for partitioning a power network into several groups of co- herent generators, and second aggregating all the generators and loads belonging to the same group, and eliminating of the rest of the buses by network reduction. The grouping method is illustrated using a 10 machines, 39 bus system (NPCC). The different areas are considered as subsystems which are connected by transmission lines, each subsystem will be rep- resented by one dynamic equivalent including a detailed ma- chine model with regulators, turbine and stabilizer and one equivalent load. If higher frequency representation is re- quired, the dynamic equivalent could be associated with an RLC circuit to reflect the frequency dependent impedance.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it